{"title":"基于优化灰色预测模型的航空发电机趋势分析","authors":"Jianguo Cui, Pengyuan Zhao, Shiliang Dong, Liqiu Liu, Rui Lv, Zhonghai Li","doi":"10.1109/ICECENG.2011.6057830","DOIUrl":null,"url":null,"abstract":"In order to accurately analyze the trend of health state variation of aero-generator, a grey prediction model based on genetic algorithm is presented in this paper. Then use the original grey model and the optimized grey model respectively to carry out health state trend analysis of the aero-generator. On this basis, the two models were used to study aero-generator health trends, and compared with the prediction result of the BP neural network, and find suitable algorithms for aero-generator health trend analysis and prediction.","PeriodicalId":6336,"journal":{"name":"2011 International Conference on Electrical and Control Engineering","volume":"4 1","pages":"3339-3342"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aero-generator trend analysis based on optimized grey prediction model\",\"authors\":\"Jianguo Cui, Pengyuan Zhao, Shiliang Dong, Liqiu Liu, Rui Lv, Zhonghai Li\",\"doi\":\"10.1109/ICECENG.2011.6057830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to accurately analyze the trend of health state variation of aero-generator, a grey prediction model based on genetic algorithm is presented in this paper. Then use the original grey model and the optimized grey model respectively to carry out health state trend analysis of the aero-generator. On this basis, the two models were used to study aero-generator health trends, and compared with the prediction result of the BP neural network, and find suitable algorithms for aero-generator health trend analysis and prediction.\",\"PeriodicalId\":6336,\"journal\":{\"name\":\"2011 International Conference on Electrical and Control Engineering\",\"volume\":\"4 1\",\"pages\":\"3339-3342\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 International Conference on Electrical and Control Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECENG.2011.6057830\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Electrical and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECENG.2011.6057830","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Aero-generator trend analysis based on optimized grey prediction model
In order to accurately analyze the trend of health state variation of aero-generator, a grey prediction model based on genetic algorithm is presented in this paper. Then use the original grey model and the optimized grey model respectively to carry out health state trend analysis of the aero-generator. On this basis, the two models were used to study aero-generator health trends, and compared with the prediction result of the BP neural network, and find suitable algorithms for aero-generator health trend analysis and prediction.
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